Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes

通过改变地表吸收的太阳辐射量，亮雪和暗森林对天气和气候有很大的影响；雪覆盖的减少或森林覆盖的增加遮盖了下层的雪，增加了对辐射的吸收，并使上面的空气变暖。因此，天气预报和气候预报的计算机模型必须通过计算地面积雪的变化质量和辐射与森林树冠的相互作用来考虑这些影响。这类模式的分辨率一般从几公里到几百公里不等。不能指望森林覆盖在如此大的距离上是连续的；相反，北方的风景是常绿和落叶森林、空地、沼泽和湖泊的马赛克。雪可以被风从开阔的地方带走，被周围的植被遮蔽，或者从森林树冠上升华，而不是到达地面，这些影响积雪模式的过程取决于洞口的大小、植被的结构和天气条件。雪本身通过提供水分、使植物和土壤免受寒冷冬季温度的影响以及储存养分来影响植被覆盖的模式。该项目的目的是开发更好的方法，在实际应用中无法分辨这些相互作用模式中的重要尺度的模型中表示雪、植被和大气之间的相互作用。我们将在北极的两个地点进行实地实验，收集有关雪、植被和辐射分布的信息：一个在瑞典，另一个在芬兰。之所以选择这些地点，是因为它们有长期的天气和降雪条件记录，很容易到达，卫星和飞机提供的植被覆盖图很好，从稀疏的落叶林到茂密的针叶林，这些都是大得多地区的典型景观。使用28个辐射计，并在每个实验过程中移动它们几次，将使我们能够测量森林中雪面上高度可变的辐射模式。来自实地试验的信息将用于开发和测试一系列模型。为了达到感兴趣的规模，我们将从一个明确解析个别树木的模型开始，并逐步以更粗的分辨率逐步完成模型，在每个阶段相互测试模型，并与观测结果进行比较。最终目标是建立一个能够更好地利用地貌信息来预测地表辐射吸收和积雪融化的模型。我们将与气候建模和预报中心的项目伙伴密切协商，以确保我们的活动能够取得符合其要求的成果。

By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. Computer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients. The aim of this project is to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions. We will gather information on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites have been chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. Using 28 radiometers, and moving them several times during the course of each experiment, will allow us to measure the highly variable patterns of radiation at the snow surface in forests. Information from the field experiments will be used in developing and testing a range of models. To reach the scales of interest, we will begin with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective is a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. We will work in close consultation with project partners at climate modelling and forecasting centres to ensure that our activities are directed towards outcomes that will meet their requirements.